Search Results for "python programming language" - Page 15

Showing 1518 open source projects for "python programming language"

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  • 1
    SentenceTransformers

    SentenceTransformers

    Multilingual sentence & image embeddings with BERT

    SentenceTransformers is a Python framework for state-of-the-art sentence, text and image embeddings. The initial work is described in our paper Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. You can use this framework to compute sentence / text embeddings for more than 100 languages. These embeddings can then be compared e.g. with cosine-similarity to find sentences with a similar meaning. This can be useful for semantic textual similar, semantic search, or paraphrase mining...
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  • 2
    DeepSeek R1

    DeepSeek R1

    Open-source, high-performance AI model with advanced reasoning

    DeepSeek-R1 is an open-source large language model developed by DeepSeek, designed to excel in complex reasoning tasks across domains such as mathematics, coding, and language. DeepSeek R1 offers unrestricted access for both commercial and academic use. The model employs a Mixture of Experts (MoE) architecture, comprising 671 billion total parameters with 37 billion active parameters per token, and supports a context length of up to 128,000 tokens. DeepSeek-R1's training regimen uniquely...
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  • 3
    Haystack

    Haystack

    Haystack is an open source NLP framework to interact with your data

    Apply the latest NLP technology to your own data with the use of Haystack's pipeline architecture. Implement production-ready semantic search, question answering, summarization and document ranking for a wide range of NLP applications. Evaluate components and fine-tune models. Ask questions in natural language and find granular answers in your documents using the latest QA models with the help of Haystack pipelines. Perform semantic search and retrieve ranked documents according to meaning...
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  • 4
    fastai

    fastai

    Deep learning library

    ... of many deep learning and data processing techniques in terms of decoupled abstractions. These abstractions can be expressed concisely and clearly by leveraging the dynamism of the underlying Python language and the flexibility of the PyTorch library. fastai is organized around two main design goals: to be approachable and rapidly productive, while also being deeply hackable and configurable. It is built on top of a hierarchy of lower-level APIs which provide composable building blocks.
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    FuseSoC

    FuseSoC

    Package manager and build abstraction tool for FPGA/ASIC development

    FuseSoC is a package manager and build abstraction tool for hardware description language (HDL) code, aimed at simplifying the development and reuse of IP cores. It provides a standardized way to describe, manage, and build hardware projects, facilitating collaboration and reducing duplication of effort in FPGA and ASIC development. ​
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  • 6
    LLMFlows

    LLMFlows

    LLMFlows - Simple, Explicit and Transparent LLM Apps

    LLMFlows is a framework for building simple, explicit, and transparent applications utilizing Large Language Models (LLMs). It emphasizes clarity and control in the development process, allowing developers to create LLM-powered applications with well-defined workflows and interactions. LLMFlows supports various LLMs and provides tools to manage prompts, responses, and application logic effectively.
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  • 7
    Medusa

    Medusa

    Framework for Accelerating LLM Generation with Multiple Decoding Heads

    Medusa is a framework aimed at accelerating the generation capabilities of Large Language Models (LLMs) by employing multiple decoding heads. This approach allows for parallel processing during text generation, significantly enhancing throughput and reducing response times. Medusa is designed to be simple to implement and integrates with existing LLM infrastructures, making it a practical solution for scaling LLM applications.
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  • 8
    Intel Extension for Transformers

    Intel Extension for Transformers

    Build your chatbot within minutes on your favorite device

    Intel Extension for Transformers is an innovative toolkit designed to accelerate Transformer-based models on Intel platforms, including CPUs and GPUs. It offers state-of-the-art compression techniques for Large Language Models (LLMs) and provides tools to build chatbots within minutes on various devices. The extension aims to optimize the performance of Transformer-based models, making them more efficient and accessible.
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  • 9
    LitGPT

    LitGPT

    20+ high-performance LLMs with recipes to pretrain, finetune at scale

    LitGPT is a collection of over 20 high-performance large language models (LLMs) accompanied by recipes to pretrain, finetune, and deploy them at scale. It provides implementations without abstractions, making it beginner-friendly while offering advanced features like flash attention and support for various precision levels. LitGPT is designed to run efficiently across multiple GPUs or TPUs, catering to both small-scale and large-scale deployments.
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  • 10
    Axolotl

    Axolotl

    Go ahead and axolotl questions

    Axolotl is a powerful and flexible framework for fine-tuning large language models on custom datasets. Built for researchers and developers, Axolotl simplifies the process of adapting LLMs for specific tasks, including chat, code generation, and instruction following. It supports a wide variety of model architectures and offers out-of-the-box optimization strategies for efficient training.
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  • 11
    OSWorld

    OSWorld

    Benchmarking Multimodal Agents for Open-Ended Tasks

    OSWorld is an open-source synthetic world environment designed for embodied AI research and multi-agent learning. It provides a richly simulated 3D world where multiple agents can interact, perform tasks, and learn complex behaviors. OSWorld emphasizes multi-modal interaction, enabling agents to process visual, auditory, and symbolic data for grounded learning in a simulated world.
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  • 12
    CRAB

    CRAB

    CRAB: Cross-environment Agent Benchmark for Multimodal Language Model

    CRAB (Composable and Reusable Autonomous Bots) is a framework for building modular, reusable AI agents that can perform complex tasks in various domains. It focuses on creating AI-driven workflows that can be composed of multiple autonomous agents working together.
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  • 13
    CloudEvents

    CloudEvents

    CloudEvents Specification

    Events are everywhere. However, event producers tend to describe events differently. The lack of a common way of describing events means developers must constantly re-learn how to consume events. This also limits the potential for libraries, tooling and infrastructure to aide the delivery of event data across environments, like SDKs, event routers or tracing systems. The portability and productivity we can achieve from event data is hindered overall. CloudEvents is a specification for...
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  • 14
    Ragas

    Ragas

    Supercharge Your LLM Application Evaluations

    Objective metrics, intelligent test generation, and data-driven insights for LLM apps. Ragas is your ultimate toolkit for evaluating and optimizing Large Language Model (LLM) applications. Say goodbye to time-consuming, subjective assessments and hello to data-driven, efficient evaluation workflows. Don't have a test dataset ready? We also do production-aligned test set generation.
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  • 15
    Backtrack Sampler

    Backtrack Sampler

    An easy-to-understand framework for LLM samplers

    Backtrack Sampler is a framework designed for experimenting with custom sampling strategies for language models (LLMs), enabling the ability to rewind and revise generated tokens. It allows developers to create and test their own token generation strategies by providing a base structure for manipulating logits and probabilities, making it a flexible tool for those interested in fine-tuning the behavior of LLMs.
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  • 16
    Haiku Sonnet for JAX

    Haiku Sonnet for JAX

    JAX-based neural network library

    Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. JAX is a numerical computing library that combines NumPy, automatic differentiation, and first-class GPU/TPU support. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX's pure function transformations. Haiku provides two core tools: a module abstraction, hk.Module...
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  • 17
    Textinator

    Textinator

    Internationalized highly customizable annotation and evaluation tool

    Textinator is an open-source internationalized highly-customizable annotation and evaluation tool for Natural Language Processing (NLP) tasks. The tool offers a web interface with a user-friendly UI and supports a number of NLP tasks out of the box. The recommended way of deploying Textinator is through building a production version of the Docker container, as described in the Deployment guidelines. Note that the production version is most definitely more secure and reliable than...
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  • 18
    AudioLM - Pytorch

    AudioLM - Pytorch

    Implementation of AudioLM audio generation model in Pytorch

    Implementation of AudioLM, a Language Modeling Approach to Audio Generation out of Google Research, in Pytorch It also extends the work for conditioning with classifier free guidance with T5. This allows for one to do text-to-audio or TTS, not offered in the paper. Yes, this means VALL-E can be trained from this repository. It is essentially the same. This repository now also contains a MIT licensed version of SoundStream. It is also compatible with EnCodec, however, be aware that it has...
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  • 19
    OpenNMT-tf

    OpenNMT-tf

    Neural machine translation and sequence learning using TensorFlow

    OpenNMT is an open-source ecosystem for neural machine translation and neural sequence learning. OpenNMT-tf is a general-purpose sequence learning toolkit using TensorFlow 2. While neural machine translation is the main target task, it has been designed to more generally support sequence-to-sequence mapping, sequence tagging, sequence classification, language modeling. Models are described with code to allow training custom architectures and overriding default behavior. For example...
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  • 20
    PyMC3

    PyMC3

    Probabilistic programming in Python

    PyMC3 allows you to write down models using an intuitive syntax to describe a data generating process. Fit your model using gradient-based MCMC algorithms like NUTS, using ADVI for fast approximate inference — including minibatch-ADVI for scaling to large datasets, or using Gaussian processes to build Bayesian nonparametric models. PyMC3 includes a comprehensive set of pre-defined statistical distributions that can be used as model building blocks. Sometimes an unknown parameter or variable...
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  • 21
    BitNet

    BitNet

    Inference framework for 1-bit LLMs

    BitNet (bitnet.cpp) is a high-performance inference framework designed to optimize the execution of 1-bit large language models, making them more efficient for edge devices and local deployment. The framework offers significant speedups and energy reductions, achieving up to 6.17x faster performance on x86 CPUs and 70% energy savings, allowing the running of models such as the BitNet b1.58 100B with impressive efficiency. With support for lossless inference and enhanced processing power, BitNet...
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  • 22
    Infinity

    Infinity

    Low-latency REST API for serving text-embeddings

    Infinity is a high-throughput, low-latency REST API for serving vector embeddings, supporting all sentence-transformer models and frameworks. Infinity is developed under MIT License. Infinity powers inference behind Gradient.ai and other Embedding API providers.
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  • 23
    BISHENG

    BISHENG

    BISHENG is an open LLM devops platform for next generation apps

    BISHENG is an open LLM application DevOps platform, focusing on enterprise scenarios. It has been used by a large number of industry-leading organizations and Fortune 500 companies. "Bi Sheng" was the inventor of movable type printing, which played a vital role in promoting the transmission of human knowledge. We hope that BISHENG can also provide strong support for the widespread implementation of intelligent applications. Everyone is welcome to participate.
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  • 24
    Chinese-LLaMA-Alpaca 2

    Chinese-LLaMA-Alpaca 2

    Chinese LLaMA-2 & Alpaca-2 Large Model Phase II Project

    This project is developed based on the commercially available large model Llama-2 released by Meta. It is the second phase of the Chinese LLaMA&Alpaca large model project. The Chinese LLaMA-2 base model and the Alpaca-2 instruction fine-tuning large model are open-sourced. These models expand and optimize the Chinese vocabulary on the basis of the original Llama-2, use large-scale Chinese data for incremental pre-training, and further improve the basic semantics and command understanding of...
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  • 25
    BERTopic

    BERTopic

    Leveraging BERT and c-TF-IDF to create easily interpretable topics

    BERTopic is a topic modeling technique that leverages transformers and c-TF-IDF to create dense clusters allowing for easily interpretable topics whilst keeping important words in the topic descriptions. BERTopic supports guided, supervised, semi-supervised, manual, long-document, hierarchical, class-based, dynamic, and online topic modeling. It even supports visualizations similar to LDAvis! Corresponding medium posts can be found here, here and here. For a more detailed overview, you can...
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